gpt-oss-120b vs Muse Spark 1.3
Updated October 21, 2026. 48 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Muse Spark 1.3 for coding: it scores 79.7 on the Vibe Coding Index against 34.5 for gpt-oss-120b.
Pick gpt-oss-120b when output tokens cost 7.1x less.
- Shared results
- 48
- gpt-oss-120b only
- 30
- Muse Spark 1.3 only
- 44
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
Muse Spark 1.3
Muse Spark 1.3 scores 79.7 against 34.5.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Muse Spark 1.3
Muse Spark 1.3 leads, 48.1 against 11.6.
Same board, both measured
Agentic work
AA Agentic Index
Muse Spark 1.3
Muse Spark 1.3 leads, 55.5 against 3.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only gpt-oss-120b has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only gpt-oss-120b has a AIME result, 92.6%.
Directional only
Knowledge
MMLU Pro
No call
Only gpt-oss-120b has a MMLU Pro result, 79.2%.
Directional only
Web design
Design Arena: websites
Muse Spark 1.3
Muse Spark 1.3 leads, 1356 against 968.
Same board, both measured
Long documents
Listed context window
Muse Spark 1.3
Muse Spark 1.3 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
gpt-oss-120b $0.0004, Muse Spark 1.3 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only gpt-oss-120b has the number, $0.51.
Directional only
At a glance
- Coding index
- gpt-oss-120b 34.5 from 2 benchmarks, Muse Spark 1.3 79.7 from 2 benchmarks.
- Widest category
- Agentic work, 53.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- Design Arena: 3D: gpt-oss-120b 901 against Muse Spark 1.3 1359, 57.3 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-120b $0.60 against Muse Spark 1.3 $4.25 per million output tokens, 7.1x apart.
- Context window
- gpt-oss-120b takes 131K tokens, Muse Spark 1.3 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | gpt-oss-120b | Bars | Muse Spark 1.3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 6 | ||
| General | 0 | 20 | ||
| All shared boards | 0 | 48 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index05
| Benchmark | gpt-oss-120b | Muse Spark 1.3 | Leader |
|---|---|---|---|
| Aider polyglot | 41.8% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified | 26.0% | Not measured | Only gpt-oss-120b measured |
| LiveBench coding | Not measured | 90.2% | Only Muse Spark 1.3 measured |
| LMArena WebDev | Not measured | 1659 | Only Muse Spark 1.3 measured |
| AA Coding Index | 30.4 | 75.8 | Muse Spark 1.3 |
| LiveCodeBench (Vals AI) | 83.2% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified (Vals AI) | 33.6% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 10.6% | Only Muse Spark 1.3 measured |
| Vibe Code Bench (Vals AI) | Not measured | 82.9% | Only Muse Spark 1.3 measured |
| Code migration (Vals AI) | Not measured | 27.6% | Only Muse Spark 1.3 measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only Muse Spark 1.3 measured |
| IOI (Vals AI) | Not measured | 43.9% | Only Muse Spark 1.3 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 72.3% | Only Muse Spark 1.3 measured |
| CyberBench (Vals AI) | Not measured | 69.4% | Only Muse Spark 1.3 measured |
| LiveCodeBench (Artificial Analysis run) | 87.8% | Not measured | Only gpt-oss-120b measured |
| SciCode | 34.0% | 59.7% | Muse Spark 1.3 |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench | 18.7% | Not measured | Only gpt-oss-120b measured |
| FrontierSWE | Not measured | 25.8% | Only Muse Spark 1.3 measured |
| WeirdML | 48.2% | Not measured | Only gpt-oss-120b measured |
| ALE-Bench | 575.6 | 1688.3 | Muse Spark 1.3 |
| LMArena Text: coding | 1379 | 1510 | Muse Spark 1.3 |
| LMArena Text: software and IT | 1387 | 1511 | Muse Spark 1.3 |
| LMArena WebDev: React | Not measured | 1672 | Only Muse Spark 1.3 measured |
| LMArena WebDev: HTML | Not measured | 1653 | Only Muse Spark 1.3 measured |
| LMArena WebDev: from an image | Not measured | 1640 | Only Muse Spark 1.3 measured |
| Neither model has a result on the other 12 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-120b | Muse Spark 1.3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.6 | 48.1 | Muse Spark 1.3 |
| Epoch Capabilities Index | 139.8 | 157.2 | Muse Spark 1.3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-120b | Muse Spark 1.3 | Leader |
|---|---|---|---|
| AA Agentic Index | 3.7 | 55.5 | Muse Spark 1.3 |
| Design Arena: agents building web apps | Not measured | 1297 | Only Muse Spark 1.3 measured |
| Design Arena: agents building full-stack apps | Not measured | 1295 | Only Muse Spark 1.3 measured |
| Design Arena: agents building mobile apps | Not measured | 1217 | Only Muse Spark 1.3 measured |
| Design Arena: agents building Godot games | Not measured | 1241 | Only Muse Spark 1.3 measured |
| Design Arena: PowerPoint slides | Not measured | 1244 | Only Muse Spark 1.3 measured |
| Design Arena: spreadsheets | Not measured | 1048 | Only Muse Spark 1.3 measured |
| LiveBench research | Not measured | 68.6% | Only Muse Spark 1.3 measured |
| LiveBench browser | Not measured | 80.0% | Only Muse Spark 1.3 measured |
| LiveBench long agentic | Not measured | 40.4% | Only Muse Spark 1.3 measured |
| Finance Agent (Vals AI) | Not measured | 58.9% | Only Muse Spark 1.3 measured |
| Tax Agent Bench (Vals AI) | Not measured | 36.0% | Only Muse Spark 1.3 measured |
| Legal Research Bench (Vals AI) | Not measured | 40.9% | Only Muse Spark 1.3 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 62.7% | Only Muse Spark 1.3 measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 4.3% | Only Muse Spark 1.3 measured |
| τ²-Bench Telecom | 65.8% | Not measured | Only gpt-oss-120b measured |
| APEX-Agents | 4.4% | 58.6% | Muse Spark 1.3 |
| METR time horizons | 56.6% | Not measured | Only gpt-oss-120b measured |
| Vending-Bench 2 | -$22 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | gpt-oss-120b | Muse Spark 1.3 | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | Not measured | Only gpt-oss-120b measured |
| LiveBench reasoning | Not measured | 89.7% | Only Muse Spark 1.3 measured |
| GPQA Diamond (Artificial Analysis run) | 78.2% | 94.1% | Muse Spark 1.3 |
| Humanity's Last Exam (Artificial Analysis run) | 19.6% | 48.7% | Muse Spark 1.3 |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only gpt-oss-120b measured |
| SimpleBench | 22.1% | Not measured | Only gpt-oss-120b measured |
| Chess puzzles | Not measured | 37.0% | Only Muse Spark 1.3 measured |
| Mystery game puzzles | 2.0% | 25.0% | Muse Spark 1.3 |
| LMArena Text: hard prompts | 1364 | 1503 | Muse Spark 1.3 |
| LMArena Text: expert | 1356 | 1519 | Muse Spark 1.3 |
| LMArena Text: hard prompts in English | 1368 | 1500 | Muse Spark 1.3 |
| LMArena Vision: diagrams | Not measured | 1330 | Only Muse Spark 1.3 measured |
| LMArena Vision: homework | Not measured | 1296 | Only Muse Spark 1.3 measured |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | gpt-oss-120b | Muse Spark 1.3 | Leader |
|---|---|---|---|
| AIME | 92.6% | Not measured | Only gpt-oss-120b measured |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only gpt-oss-120b measured |
| MGSM (Vals AI) | 92.0% | Not measured | Only gpt-oss-120b measured |
| AA Math Index | 93.4 | Not measured | Only gpt-oss-120b measured |
| AIME 2025 (Artificial Analysis run) | 93.4% | Not measured | Only gpt-oss-120b measured |
| OTIS Mock AIME | 88.9% | 99.2% | Muse Spark 1.3 |
| FrontierMath, tiers 1 to 3 | Not measured | 74.4% | Only Muse Spark 1.3 measured |
| FrontierMath, tier 4 | Not measured | 46.3% | Only Muse Spark 1.3 measured |
| ProofBench | Not measured | 58.0% | Only Muse Spark 1.3 measured |
| LMArena Text: math | 1389 | 1497 | Muse Spark 1.3 |
| LMArena Text: mathematical work | 1386 | 1491 | Muse Spark 1.3 |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | gpt-oss-120b | Muse Spark 1.3 | Leader |
|---|---|---|---|
| MMLU Pro | 79.2% | Not measured | Only gpt-oss-120b measured |
| LegalBench (Vals AI) | 75.9% | Not measured | Only gpt-oss-120b measured |
| CaseLaw (Vals AI) | 48.8% | Not measured | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | 58.2% | Not measured | Only gpt-oss-120b measured |
| TaxEval (Vals AI) | 71.6% | Not measured | Only gpt-oss-120b measured |
| MedQA (Vals AI) | 91.4% | Not measured | Only gpt-oss-120b measured |
| MMLU Pro (Artificial Analysis run) | 80.8% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: science | 1382 | 1507 | Muse Spark 1.3 |
| LMArena Text: medicine and healthcare | 1388 | 1493 | Muse Spark 1.3 |
| LMArena Text: legal and government | 1355 | 1499 | Muse Spark 1.3 |
| LMArena Text: business and finance | 1359 | 1490 | Muse Spark 1.3 |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | gpt-oss-120b | Muse Spark 1.3 | Leader |
|---|---|---|---|
| Design Arena: websites | 968 | 1356 | Muse Spark 1.3 |
| Design Arena: UI components | 927 | 1352 | Muse Spark 1.3 |
| Design Arena: game dev | 992 | 1329 | Muse Spark 1.3 |
| Design Arena: data viz | 987 | 1343 | Muse Spark 1.3 |
| Design Arena: 3D | 901 | 1359 | Muse Spark 1.3 |
| Design Arena: all code categories | 963 | 1353 | Muse Spark 1.3 |
| Design Arena: SVG | Not measured | 1300 | Only Muse Spark 1.3 measured |
| Design Arena: ASCII art | Not measured | 1280 | Only Muse Spark 1.3 measured |
| LiveBench design | Not measured | 74.8% | Only Muse Spark 1.3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index020
| Benchmark | gpt-oss-120b | Muse Spark 1.3 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 79.6% | Only Muse Spark 1.3 measured |
| IFBench | 69.0% | Not measured | Only gpt-oss-120b measured |
| Long context reasoning (AA-LCR) | 52.0% | 83.0% | Muse Spark 1.3 |
| DTBench | 76.3% | 96.5% | Muse Spark 1.3 |
| LMCA | 22.1% | 53.9% | Muse Spark 1.3 |
| Fiction.LiveBench | 44.4% | Not measured | Only gpt-oss-120b measured |
| Creative writing (Lech Mazur) | 77.1% | Not measured | Only gpt-oss-120b measured |
| Surface Evolver Bench | 25.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text | 1366 | 1490 | Muse Spark 1.3 |
| LMArena Text: instruction following | 1318 | 1479 | Muse Spark 1.3 |
| LMArena Text: creative writing | 1274 | 1462 | Muse Spark 1.3 |
| LMArena Vision | Not measured | 1308 | Only Muse Spark 1.3 measured |
| LMArena Text: English | 1375 | 1495 | Muse Spark 1.3 |
| LMArena Text: non-English | 1351 | 1481 | Muse Spark 1.3 |
| LMArena Text: Chinese | 1385 | 1532 | Muse Spark 1.3 |
| LMArena Text: German | 1353 | 1513 | Muse Spark 1.3 |
| LMArena Text: Japanese | 1331 | 1470 | Muse Spark 1.3 |
| LMArena Text: Korean | 1282 | 1490 | Muse Spark 1.3 |
| LMArena Text: French | 1370 | 1511 | Muse Spark 1.3 |
| LMArena Text: Spanish | 1389 | 1496 | Muse Spark 1.3 |
| LMArena Text: Russian | 1343 | 1491 | Muse Spark 1.3 |
| LMArena Text: Polish | 1353 | 1490 | Muse Spark 1.3 |
| LMArena Text: multi-turn | 1340 | 1487 | Muse Spark 1.3 |
| LMArena Text: longer queries | 1319 | 1488 | Muse Spark 1.3 |
| LMArena Text: writing and language | 1306 | 1470 | Muse Spark 1.3 |
| LMArena Text: entertainment and media | 1292 | 1457 | Muse Spark 1.3 |
| LMArena Vision: English | Not measured | 1298 | Only Muse Spark 1.3 measured |
| LMArena Vision: Chinese | Not measured | 1384 | Only Muse Spark 1.3 measured |
| LMArena Vision: reading text | Not measured | 1319 | Only Muse Spark 1.3 measured |
| LMArena Vision: humor | Not measured | 1293 | Only Muse Spark 1.3 measured |
| LMArena Vision: creative writing | Not measured | 1296 | Only Muse Spark 1.3 measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-120b | Muse Spark 1.3 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
gpt-oss-120b costs less
Repository review
50K input + 3K output tokens
gpt-oss-120b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-120b costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI gpt-oss-120b | Meta Muse Spark 1.3 |
|---|---|---|
| Maker | OpenAI | Meta |
| Weights | Open weights | No public weights listed |
| Released | August 5, 2025 | September 2, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.15 | $1.25 |
| Output $/Mtok | $0.60 | $4.25 |
| Coding index | 34.5 | 79.7 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.51 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-120b better than Muse Spark 1.3 for coding?
Pick Muse Spark 1.3 for coding: it scores 79.7 on the Vibe Coding Index against 34.5 for gpt-oss-120b. Pick gpt-oss-120b when output tokens cost 7.1x less.
Which is cheaper, gpt-oss-120b or Muse Spark 1.3?
gpt-oss-120b costs $0.15 per million input tokens and $0.60 per million output tokens; Muse Spark 1.3 costs $1.25 and $4.25. Cost per solved task is known for gpt-oss-120b only.
Which has the bigger context window, gpt-oss-120b or Muse Spark 1.3?
Muse Spark 1.3, with 1.05M tokens against 131K.
How many benchmarks is the gpt-oss-120b vs Muse Spark 1.3 comparison based on?
48 benchmarks have a result for both models as of October 21, 2026. gpt-oss-120b's coding index rests on 2 independent benchmarks and Muse Spark 1.3's on 2. Where only one model has a result, the page says so instead of naming a winner.